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cs.AI2024
OML: A Primitive for Reconciling Open Access with Owner Control in AI Model Distribution
Zerui Cheng, Edoardo Contente, Ben Finch +9
The current paradigm of AI model distribution presents a fundamental dichotomy: models are either closed and API-gated, sacrificing transparency and local execution, or openly dist…
cs.LG2024
PLeaS -- Merging Models with Permutations and Least Squares
Anshul Nasery, Jonathan Hayase, Pang Wei Koh +1
The democratization of machine learning systems has made the process of fine-tuning accessible to practitioners, leading to a wide range of open-source models fine-tuned on special…